SOTAVerified

Autonomous Vehicles

Autonomous vehicles is the task of making a vehicle that can guide itself without human conduction.

Many of the state-of-the-art results can be found at more general task pages such as 3D Object Detection and Semantic Segmentation.

( Image credit: GSNet: Joint Vehicle Pose and Shape Reconstruction with Geometrical and Scene-aware Supervision )

Papers

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Showing 1301–1310 of 2605 papers

TitleStatusHype
On the utilization of Macroscopic Information for String Stability of a Vehicular Platoon—0
On Transferability of Driver Observation Models from Simulated to Real Environments in Autonomous Cars—0
Open-Set LiDAR Panoptic Segmentation Guided by Uncertainty-Aware Learning—0
Open vs Closed-ended questions in attitudinal surveys -- comparing, combining, and interpreting using natural language processing—0
Open-World Panoptic Segmentation—0
Operationalizing Machine Learning: An Interview Study—0
Opportunistic Collaborative Planning with Large Vision Model Guided Control and Joint Query-Service Optimization—0
Optical Flow Matters: an Empirical Comparative Study on Fusing Monocular Extracted Modalities for Better Steering—0
Optimal Actuator Attacks on Autonomous Vehicles Using Reinforcement Learning—0
Optimal Control of Autonomous Vehicles Approaching A Traffic Light—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1BAAMA3DP22.85—Unverified
2GSNetA3DP20.21—Unverified